製药的巨量资料 - Strategic Intelligence
市场调查报告书
商品编码
1617669

製药的巨量资料 - Strategic Intelligence

Strategic Intelligence: Big Data in Pharma

出版日期: | 出版商: GlobalData | 英文 66 Pages | 订单完成后即时交付

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整个製药业正在广泛产生大数据

全球製药领域从各种来源产生大量数据,包括病患登记、临床试验和穿戴式技术。这些资料集如此庞大、复杂且非结构化,传统的大数据分析方法在处理它们时效率低。

因此,製药业正在大数据分析技术方面进行创新,这些技术可以保护、储存、处理、分析、聚合和整合大量复杂的资料集,以产生新的见解。此外,这些技术可以透过机器学习(ML)、人工智慧、物联网、数位孪生等来实现。

本报告提供了全球製药业的研究和分析,包括有关医疗、宏观经济、技术和监管趋势将如何影响製药业大数据的最新见解和预测,我们提供了对关键参与者和未来颠覆者的见解。

目录

图表的清单

表的清单

  • 参与企业
  • 题目的简报
  • 趋势
  • 产业分析
  • 价值链
  • 企业
  • 医药品製造计分卡
  • 简称
  • 参考文献
  • 关于作者
  • 题目的调查手法
Product Code: GDHCHT534

Big data is generated extensively across pharma

The international pharmaceutical landscape generates vast amounts of data from a variety of sources, such as patient registries, clinical trials, wearable technologies, and more. Such datasets are extremely vast, complex, and unstructured, rendering traditional big data analytical methodologies inefficient for processing.

As a result, organizations within the pharmaceutical industry are innovating big data analytical technologies that can secure, store, process, analyze, aggregate, and integrate vast and complex datasets for the purpose of acquiring novel insights. Furthermore, these technologies can be implemented with machine learning (ML), artificial intelligence (AI), Internet of Things (IoT), digital twins, and more.

This report consolidates GlobalData's latest thinking and forecasts around how the healthcare, macroeconomic, technology, and regulatory trends will impact the big data in pharma space, as well as providing insights into the leading players and future disruptors across the value chain, and providing insights into key drugs and markets from GlobalData's Pharma Intelligence Center. Additionally, this report is designed to provide strategic planners, competitive intelligence professionals and key stakeholders in the pharmaceutical industry a clear view of the opportunities and risks over the foreseeable future for big data.

Scope

  • A dedicated report examining the pivotal healthcare, technological, macroeconomic, and regulatory trends shaping the big data in pharma landscape. This report also provides an in-depth analysis of how these trends are poised to either accelerate progress or create obstacles for the growth of the big data market.

Reasons to Buy

  • Understand the key trends accelerating or hindering the big data in pharma space.
  • See market forecasts for different therapies within big data up to 2028.
  • Understand recent and influential developments in big data.
  • Review of leaders and disruptors across the big data value chain.

Table of Contents

Table of Contents

List of Figures

List of Tables

  • Players
  • Thematic Briefing
  • Trends
  • Industry Analysis
  • Value Chain
  • Companies
  • Drug Manufacturing Scorecard
  • Abbreviations
  • Further Reading
  • About the Authors
  • Our Thematic Research Methodology

List of Tables

  • Table 1: Healthcare trends in the big data space
  • Table 2: Technology trends in the big data space
  • Table 3: Macroeconomic trends in the big data space
  • Table 4: Regulatory trends in the big data space
  • Table 5: Examples of M&A in the big data and pharma spaces, 2022-24
  • Table 6: Examples of strategic partnerships in the pharma big data space, 2022-24
  • Table 7: Examples of large funding deals in the big data space since 2022
  • Table 8: Drug target discovery big data analytical tools
  • Table 9: VCT big data analytical tools
  • Table 10: Precision medicine big data analytical tools
  • Table 11: Digital twins big data analytical tools
  • Table 12: Telemedicine big data analytical tools
  • Table 13: Digital biomarkers big data analytical tools
  • Table 14: Genomics integration within the big data space
  • Table 15: Examples of leading big data vendors within the big data theme
  • Table 16: Examples of specialist big data vendors in the big data theme
  • Table 17: Examples of leading big data adopters in the big data theme
  • Table 18: GlobalData reports
  • Table 19: Target identification and validation
  • Table 20: The time taken to identify novel drug targets.
  • Table 21: The different platforms and libraries used for drug repurposing
  • Table 22: The leading technology players within the AI in drug discovery theme and summarizes their competitive position
  • Table 13: The specialist AI vendors in drug discovery and summarizes their competitive position
  • Table 24: The leading adopters of AI in drug discovery and summarizes their competitive position
  • Table 25: Abbreviations
  • Table 26: GlobalData reports

List of Figures

  • Figure 1: Who are the leading players in the big data pharma space?
  • Figure 2: Pharma contributed 1.1% of the total global data and analytics market in 2022
  • Figure 3: Pharma will contribute 1.1% of the total global data and analytics market in 2028
  • Figure 4: The total global data and analytics market for pharma was valued at $1.1B in 2022, led by China
  • Figure 5: China will lead the global data and analytics market in pharma in 2028
  • Figure 6: Confidence levels in big data's potential to transform the pharmaceutical industry
  • Figure 7: Key pharmaceutical value chain components poised to benefit most from big data
  • Figure 8: Big data trends in GlobalData's social media analytics database, September 2023 - September 2024
  • Figure 9: Examples of top posts related to big data, 2023-24
  • Figure 10: The big data value chain in pharma
  • Figure 11: Who does what in the drug manufacturing space?
  • Figure 12: Our thematic screen ranks companies based on overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of future performance
  • Figure 13: Our valuation screen ranks our universe of companies within a sector based on selected valuation metrics
  • Figure 14: Our risk screen ranks companies within a particular sector based on overall investment risk